Land cover, as its name implies, shows the "covering" of the landscape. This is different from land use, which is what is permitted, practiced or intended for a given place. For example, a "forested" land cover area as detected by the satellite may appear as "rural residential" or "open space" on a town zoning map. CLEAR's land cover information comes from remotely sensed imagery from satellites, in this case several of the Landsat satellite series. Sensors aboard the satellite collect (sense) light in a number of different wavelengths that is reflected from the surface of the earth. The data are converted via computer programs and human expertise into land cover maps made up of many pieces, or pixels, of information that are 30 meters (or about 100 feet) square. Although remotely sensed land cover maps have been around for quite some time, comparing different land cover datasets has been difficult. Satellite sensors are continually evolving along with the land cover information derived from them. Land cover derived from images from different years taken by different sensors (and perhaps at different times of the year) normally cannot be compared directly with any claim of accuracy. CLEAR's challenge was to solve this "apples and oranges" problem by using a technique called "cross-correlation analysis." This allows us to provide state citizens and decision makers with reliable, comparable information which shows how Connecticut's landscape has changed over the last 30 years. Maps from seven dates (1985, 1990, 1995, 2002, 2006, 2010 and 2015) were created, and can be explored in various ways on this website.
The FGDC (Federal Geographic Data Committee) has a standard form for reporting metadata, or information about data. Visit the FGDC-compliant metadata for: